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http://genome.jgi.doe.gov/

Portal providing access to all JGI genomic databases and analytical tools, sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web.

Proper citation: JGI Genome Portal (RRID:SCR_002383) Copy   

•   Source: SciCrunch Registry

https://www.genevestigator.com/gv/

A high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.

Proper citation: Genevestigator (RRID:SCR_002358) Copy   

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http://www.cmhd.ca/genetrap/

Generate gene trap insertions using mutagenic polyA trap vectors, followed by sequence tagging to develop a library of mutagenized ES cells freely available to the scientific community. This library is searchable by sequence or key word searches including gene name or symbol, chromosome location, or Gene Ontology (GO) terms. In addition,they offer a custom email alert service in which researchers are able to submit search criteria. Researchers will receive automated e-mail notification of matching gene trap clones as they are entered into the library and database. The resource features the use of complementary second and third generation polyA trap vectors developed by the Stanford lab and the laboratory of Professor Yasumasa Ishida of the Nara Institute of Science and Technology (NAIST) in Japan to mutagenize murine embryonic stem (ES) cells. CMHD gene trap clones are distributed by the Canadian Mouse Mutant Repository(CMMR). Information about ordering, services, and pricing can be found on their web site (http://www.cmmr.ca/services/index.html)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: Centre for Modeling Human Disease Gene Trap Resource (RRID:SCR_002785) Copy   

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http://reflect.embl.de/

Web service that tags gene, protein, and small molecule names in any web page. Clicking on a tagged term opens a small popup showing summary information, and allows the user to quickly link to more detailed information. For each protein or gene, Reflect provides domain structure, sub-cellular localization, 3D structure, and interaction partners. For small molecules, it provides the chemical structure and interaction partners. Reflect can be installed as a plugin to Firefox or Internet Explorer, or can be used by entering a URL in the field provided. It can also be accessed programmatically via a REST or SOAP API, and a Reflect button can easily be added to any web page using Javascript or using a CGI proxy. Reflect was first-prize winner out of over 70 submissions in the Elsevier Grand Challenge, an international competition for systems that improve the way scientific information is communicated and used. Reflect can be edited and improved by the community.

Proper citation: Reflect (RRID:SCR_002714) Copy   

•   Source: SciCrunch Registry

http://camera.calit2.net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016; however, the URL provides links to associated projects and data. A suite of data query, download, upload, analysis and sharing tools serving the needs of the microbial ecology research community, and other scientists using metagenomics data.

Proper citation: Community Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis (RRID:SCR_002676) Copy   

•   Source: SciCrunch Registry

http://www.g2conline.org/

Genes to Cognition (G2C) Online is about modern neuroscience. It focuses on cognitive disorders, cognitive processes, and research approaches. Use the dynamic network maps to explore our library of 750+ unique items. Or, use the linear Selected Items menu on top of each map to tour selected content. Read the G2C blog, use simple mapper, or the 3-D brain, an interactive model of the brain. Disorders included in this site: ADHD, Alzheimer's Disease, Autism, Bipolar Disorder, Depression, Schizophrenia Cognitive Processes include: Attention, Language, Learning and Memory, Perception, and Thinking Research Approaches include: Bioinformatics, Ethics, Gene Finding, Model systems, Neuroimaging, Psychology. Navigation: Interact with the dynamic Networks Maps to explore the full catalog of content. Roll-over a node on the map for a preview and click to open the content. Move on to other content by returning to the network map. Each node you visit on the map gets flagged. Follow the Selected Items Subway Line for an overview of a topic. Roll-over a subway node for a preview and click to open the content. Other Features: Most content items include links to Related Items, which allow you to explore further. The Glossary includes over 300 neuroscience keywords. Search for content using keywords or id number. Select a preferred network map to view the content in context. Open/close the History at the lower left to view visited content. Your history is stored until you clear it. Simple Mapper - We developed Simple Mapper to power this web site on the brain. Now, you can use it to organize what comes out of yours! With Simple Mapper create and save concept maps, network diagrams, or flowcharts for personal use or to share with others. 3-D Brain - The G2C Brain is an interactive 3-D model of the brain, with 29 structures that can be rotated in three-dimensional space. Each structure has information on brain disorders, brain damage, case studies, and links to modern neuroscience research. Ideal for students, researchers, and educators in psychology and biology. Also available for download: 3D Brain App for iPhone and iPod Touch!

Proper citation: Genes to Cognition Online (RRID:SCR_002746) Copy   

•   Source: SciCrunch Registry

http://snpeff.sourceforge.net/

Genetic variant annotation and effect prediction software toolbox that annotates and predicts effects of variants on genes (such as amino acid changes). By using standards, such as VCF, SnpEff makes it easy to integrate with other programs.

Proper citation: SnpEff (RRID:SCR_005191) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Rebholz-srv/ebimed/

A web application that combines Information Retrieval and Extraction from Medline. EBIMed finds Medline abstracts in the same way PubMed does. Then it goes a step beyond and analyses them to offer a complete overview on associations between UniProt protein/gene names, GO annotations, Drugs and Species. The results are shown in a table that displays all the associations and links to the sentences that support them and to the original abstracts. By selecting relevant sentences and highlighting the biomedical terminology EBIMed enhances your ability to acquire knowledge, relate facts, discover implications and, overall, have a good overview economizing the effort in reading.

Proper citation: EBIMed (RRID:SCR_005314) Copy   

•   Source: SciCrunch Registry

http://ikmbio.csie.ncku.edu.tw/coin/home.php

A web-based system that assess articles according to their term correlations among sentences. It employs the co-occurrence relations and their network centralities to evaluate the influence of biomedical terms from Comparative Toxicogenomics Database (CTD)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CoIN (RRID:SCR_005332) Copy   

•   Source: SciCrunch Registry

http://en.wikipedia.org/wiki/Gene_Wiki

The Gene Wiki is a project that facilitates transferring information on human genes to Wikipedia article stubs with the goal of promoting collaboration and expansion of the articles. Number of gene articles The human genome contains an estimated 20,00025,000 protein-coding genes. The goal of the Gene Wiki project is to create seed articles for every notable human gene, that is, every gene whose function has been assigned in the peer-reviewed scientific literature. Approximately half of human genes have assigned function, therefore the total number of articles seeded by the Gene Wiki project would be expected to be in the range of 10,000 - 15,000. To date, approximately 10,271 articles have been created or augmented to include Gene Wiki project content. Expansion Once seed articles have been established, the hope and expectation is that these will be annotated and expanded by editors ranging in experience from the lay audience to students to professionals and academics. Proteins encoded by genes The majority of genes encode proteins hence understanding the function of a gene generally requires understanding of the function of the corresponding protein. In addition to including basic information about the gene, the project therefore also includes information about the protein encoded by the gene. Stubs for the Gene Wiki project are created by a bot and contain links to the following primary gene/protein databases * HUGO Gene Nomenclature Committee official gene name * Entrez Gene database * OMIM (Mendelian Inheritance in Man) database that catalogues all the known diseases with a genetic component * Amigo Gene Ontology * HomoloGene gene homologs in other species * SymAtlasRNA gene expression pattern in tissues * Protein Data Bank 3D structure of protein encoded by the gene * Uniprot (universal protein resource) a central repository of protein data

Proper citation: Gene Wiki (RRID:SCR_005317) Copy   

•   Source: SciCrunch Registry

http://enigma.ini.usc.edu/

Network that brings together researchers in imaging genomics, to understand brain structure and function, based on MRI, DTI, fMRI and genomewide association scan (GWAS) data. The ENIGMA Network has several goals: * to create a network of like-minded individuals, interested in pushing forward the field of imaging genetics * to ensure promising findings are replicated via member collaborations, in order to satisfy the mandates of most journals * to share ideas, algorithms, data, and information on promising findings or methods * to facilitate training, including workshops and conferences on key methods and emerging directions in imaging genetics. Data sharing with other members of the ENIGMA Network is optional and by no means a requirement of joining the network. Genetics and Imaging Protocols are available.

Proper citation: ENIGMA: Enhancing Neuro Imaging Genetics Through Meta-Analysis (RRID:SCR_005515) Copy   

•   Source: SciCrunch Registry

http://nlmfoundation.org/

The primary mission of the Nancy Lurie Marks (NLM) Family Foundation is to help people with autism lead fulfilling and rewarding lives. The Foundation is committed to understanding autism from a scientific perspective, increasing opportunities and services available to the autism community and educating the public about autism. In pursuit of its mission, the Foundation develops and provides grants to programs in research, clinical care, policy, advocacy and education. Founded by Nancy Lurie Marks over 25 years ago, the NLM Family Foundation is one of the largest supporters of initiatives in these areas. The principal goal of the scientific program is to achieve a deeper understanding of the biological basis of autism, focusing on genetics, synaptic chemistry, the neurobiology of communication, systems biology and the physiology of movement. The Foundation funds peer-reviewed research, the development of collaborative investigator projects, and research fellowship programs. Through sponsorship of scientific conferences, symposia and workshops, the Foundation seeks to encourage innovation and provide a springboard to generate new avenues of shared inquiry. The NLM Family Foundation supports programs which focus on novel ways to improve the communication and social abilities of those with autism. Other programs are designed to increase advocacy for legal rights and access to support services for persons with autism, and to increase community understanding and openness to inclusion through education and documentary films.

Proper citation: Nancy Lurie Marks Family Foundation (RRID:SCR_005455) Copy   

•   Source: SciCrunch Registry

http://cgap.nci.nih.gov/Genes/GOBrowser

With the CGAP GO browser, you can browse through the GO vocabularies, and find human and mouse genes assigned to each term. GO data updated every few months. Platform: Online tool

Proper citation: CGAP GO Browser (RRID:SCR_005676) Copy   

•   Source: SciCrunch Registry

http://vortex.cs.wayne.edu/projects.htm#Onto-Express

The typical result of a microarray experiment is a list of tens or hundreds of genes found to be differentially regulated in the condition under study. Independently of the methods used to select these genes, the common task faced by any researcher is to translate these lists of genes into a better understanding of the biological phenomena involved. Currently, this is done through a tedious combination of searches through the literature and a number of public databases. We developed Onto-Express (OE) as a novel tool able to automatically translate such lists of differentially regulated genes into functional profiles characterizing the impact of the condition studied. OE constructs functional profiles (using Gene Ontology terms) for the following categories: biochemical function, biological process, cellular role, cellular component, molecular function and chromosome location. Statistical significance values are calculated for each category. We demonstrated the validity and the utility of this comprehensive global analysis of gene function by analyzing two breast cancer data sets from two separate laboratories. OE was able to identify correctly all biological processes postulated by the original authors, as well as discover novel relevant mechanisms (Draghici et.al, Genomics, 81(2), 2003). Other results obtained with Onto-Express can be found in Khatri et.al., Genomics. 79(2), 2002. Custom level of abstraction of the Gene Ontology. User account required. Platform: Online tool

Proper citation: Onto-Express (RRID:SCR_005670) Copy   

•   Source: SciCrunch Registry

http://www.genetools.us

Web-service providing access to database that brings together information from broad range of resources. Web application for functional annotation and statistical hypothesis testing. Provides tools for analysis of genomic and microarray data. Collection of tools include Bibliographic Information,Databases,Gene Annotation,Gene Regulation, Microarray,Proteins,Sequence Manipulation - Nucleic Acids,Sequence Manipulation - Protein, Systems Biology.

Proper citation: GeneTools (RRID:SCR_005663) Copy   

•   Source: SciCrunch Registry

http://manatee.sourceforge.net/

Manatee is a web-based gene evaluation and genome annotation tool; Manatee can store and view annotation for prokaryotic and eukaryotic genomes. The Manatee interface allows biologists to quickly identify genes and make high quality functional assignments, such as GO classifications, using search data, paralogous families, and annotation suggestions generated from automated analysis. Manatee can be downloaded and installed to run under the CGI area of a web server, such as Apache. Platform: Online tool, Linux compatible, Solaris

Proper citation: Manatee (RRID:SCR_005685) Copy   

•   Source: SciCrunch Registry

http://genenet2.uthsc.edu/geneinfoviz/search.php

GeneInfoViz is a web based tool for batch retrieval of gene function information, visualization of GO structure and construction of gene relation networks. It takes a input list of genes in the form of LocusLink ID, UniGeneID, gene symbol, or accession number and returns their functional genomic information. Based on the GO annotations of the given genes, GeneInfoViz allows users to visualize these genes in the DAG structure of GO, and construct a gene relation network at a selected level of the DAG. Platform: Online tool

Proper citation: GeneInfoViz (RRID:SCR_005680) Copy   

•   Source: SciCrunch Registry

http://sybil.sourceforge.net/

A web-based software package for comparative genomics.

Proper citation: Sybil (RRID:SCR_005593) Copy   

•   Source: SciCrunch Registry

https://github.com/transmart

tranSMART is a knowledge management platform that enables scientists to develop and refine research hypotheses by investigating correlations between genetic and phenotypic data, and assessing their analytical results in the context of published literature and other work. tranSMART is licensed through GPL 3. The integration, normalization, and alignment of data in tranSMART permits users to explore data very efficiently to formulate new research strategies. Some of tranSMART''s specific applications include: * Revalidating previous hypotheses * Testing and refining novel hypotheses * Conducting cross-study meta-analysis * Searching across multiple data sources to find associations of concepts, such as a gene''s involvement in biological processes or experimental results * Comparing biological processes and pathways among multiple data sets from related diseases or even across multiple therapeutic areas Data Repository The tranSMART Data Repository combines a data warehouse with access to federated sources of open and commercial databases. tranSMART accommodates: * Phenotypic data, such as demographics, clinical observations, clinical trial outcomes, and adverse events * High content biomarker data, such as gene expression, genotyping, pharmacokinetic and pharmaco-dynamics markers, metabolomics data, and proteomics data * Unstructured text-data, such as published journal articles, conference abstracts and proceedings, and internal studies and white papers * Reference data from sources such as MeSH, UMLS, Entrez, GeneGo, Ingenuity, etc. * Metadata providing context about datasets, allowing users to assess the relevance of results delivered by tranSMART Data in tranSMART is aligned to allow identification and analysis of associations between phenotypic and biomarker data, and it is normalized to conform with CDISC and other standards to facilitate search and analysis across different data sources. tranSMART also enables investigators to search published literature and other text sources to evaluate their analysis in the context of the broader universe of reported research. External data can also be integrated into the tranSMART data repository, either from open data projects like GEO, EBI Array Express, GCOD, or GO, or from commercially available data sources. Making data accessible in tranSMART enables organizations to leverage investments in manual curation, development costs of automated ETL tools, or commercial subscription fees across multiple research groups. Dataset Explorer tranSMART''s Dataset Explorer provides flexible, powerful search and analysis capabilities. The core of the Dataset Explorer integrates and extends the open source i2b2 application, Lucene text indexing, and GenePattern analytical tools. Connections to other open source and commercial analytical tools such as Galaxy, Integrative Genomics Viewer, Plink, Pathway Studio, GeneGo, Spotfire, R, and SAS can be established to expand tranSMART''s capabilities. tranSMART''s design allows organizations flexibility in selecting analytical tools accessible through the Dataset Explorer, and provides file export capabilities to enable researchers to use tools not accessible in the tranSMART portal.

Proper citation: tranSMART (RRID:SCR_005586) Copy   

•   Source: SciCrunch Registry

http://basalganglia.huji.ac.il/links.htm

GOdist is a Matlab program that analyzes Affymetrix microarray expression data implementing Kolmogorov-Smirnov (KS) continuous statistics approach. It also implements the discrete approach using Fisher exact test employing a two-tailed hypergeometric distribution. GOdist enables detection of both kinds of changes within specific GO terms represented on the array in relation to different populations: the global array population, the direct parents of the analyzed GO term and the global parent of it (e.g. biological process, molecular function or cellular component). Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOdist (RRID:SCR_005770) Copy   

•   Source: SciCrunch Registry